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A fast low-density parity-check code simulator based on compressed parity-check matrices

机译:基于压缩奇偶校验矩阵的快速低密度奇偶校验代码模拟器

摘要

Low-density parity-check (LDPC) codes are very powerful error-correction codes with capabilities approaching the Shannon's limits. In evaluating the error performance of an LDPC code, the computer simulation time taken becomes a primary concern when tens of millions of noise-corrupted codewords are to be decoded, particularly for codes with very long lengths. In this paper, we propose modeling the parity-check matrix of an LDPC code with compressed parity-check matrices in the check-node domain (CND) and in the bit-node domain (BND), respectively. Based on the compressed parity-check matrices, we created two message matrices, one in the CND and another in the BND, and two domain conversion matrices, one from CND to BND and another from BND to CND. With the proposed message matrices, the data used in the iterative LDPC decoding algorithm can be closely packed and stored within a small memory size. Consequently, such data can be mostly stored in the cache memory, reducing the need for the central processing unit to access the random access memory and hence improving the simulation time significantly. Furthermore, the messages in one domain can be easily converted to another domain with the use of the conversion matrices, facilitating the central processing unit to access and update the messages.
机译:低密度奇偶校验(LDPC)码是非常强大的纠错码,具有接近香农极限的能力。在评估LDPC码的错误性能时,当要解码数千万个受噪声破坏的代码字时,尤其是对于长度很长的代码,花费的计算机仿真时间成为首要考虑因素。在本文中,我们提议分别在校验节点域(CND)和位节点域(BND)中使用压缩的奇偶校验矩阵对LDPC码的奇偶校验矩阵进行建模。基于压缩的奇偶校验矩阵,我们创建了两个消息矩阵,一个在CND中,另一个在BND中,以及两个域转换矩阵,一个从CND到BND,另一个从BND到CND。利用所提出的消息矩阵,可以将LDPC迭代解码算法中使用的数据紧密打包并存储在较小的内存中。因此,这样的数据可以大部分存储在高速缓冲存储器中,从而减少了中央处理单元访问随机存取存储器的需要,从而显着缩短了仿真时间。此外,使用转换矩阵可以容易地将一个域中的消息转换为另一域,从而有利于中央处理单元访问和更新消息。

著录项

  • 作者

    Yau SF; Wong TL; Lau FCM; He Y;

  • 作者单位
  • 年度 2013
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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